Students will learn data science to utilize vast and diverse data for business, and acquire applied skills in data analysis. In particular, we will lecture on the characteristics of unstructured data and their analysis methods, keeping in mind its application technology management, and acquire applied skills in data analysis through programming exercises.
The goals of this course are as follows:
- To understand the basics of text analysis, network analysis, deep learning, and reinforcement learning
- To be able to apply these methods to unstructured data for the creation of new businesses
Text, morphological analysis, sentiment analysis, social network analysis, neural networks, deep learning, reinforcement learning
|✔ Specialist skills||Intercultural skills||Communication skills||Critical thinking skills||✔ Practical and/or problem-solving skills|
We will lecture on the basics of text analysis, network analysis, and deep learning for unstructured data (text, network, images, etc.), and through programming exercises, students will solidify their understanding and develop practical skills for data analysis (using Python and R). In addition, we will invite a corporate data scientist to lecture and to have a discussion on the cutting-edge applications of data science in business.
|Course schedule||Required learning|
|Class 1||Network analysis||Understand the nature of network data, theories and methods for visualizing and analyzing networks|
|Class 2||Text analysis||Understand the nature of text data, principles and methods of text analysis, such as morphological analysis and sentiment analysis|
|Class 3||Programming exercise (1)||Acquire programming skills for text analysis and network analysis|
|Class 4||Deep learning||Understand the principles of deep learning and the methods for its application to unstructured data|
|Class 5||Reinforcement learning||Understand the principles of reinforcement learning and the methods for its application to unstructured data|
|Class 6||Programming exercise (2)||Acquire programming skills related to deep learning and reinforcement learning|
|Class 7||Guest lecture||Gain knowledge about cutting-edge data science applications in business|
After the lecture, it is recommended to read and review the relevant sections of the reference books.
Slides will be provided.
Albert-Laszlo Barabasi, Network Science, Cambridge University Press (2016)
Class contribution 20%, Exercise 40%, Report 40%